Assessment of local feasible renewable energy-based heating/cooling utilisation for Brasov (D2.2)

Transcription

1 Assessment of local feasible renewable energy-based heating/cooling utilis for Brasov (D2.2) Prepared by: Richard Büchele (TU ien Energy Economics Group) Reviewed by: Marcus Hummel (TU ien Energy Economics Group) Camelia Rata (Agentia Pentru Management ul Energiei si Protectia Mediului Brasov) Date: 14/11/2016

2 The progressheat project D2.2 - Assessment of local feasible RES-H/C utilis The progressheat project aims at assisting policy makers at the local, regional, nal and EU-level in developing integrated, effective and efficient policy strategies to achieve a rapid and widespread penetr of renewable and efficient heating and cooling systems. Together with 6 local authorities in 6 target countries across Europe (AT, DE, CZ, DK, PT, RO), heating and cooling strategies will be developed by a detailed analysis of (1) heating and cooling demands and future developments, (2) long-term potentials of renewable energies and waste heat in the regions, (3) barriers & drivers and (4) a model-based assessment of policy intervention in scenarios up to progressheat will assist nal policy makers to implement the right policies based on a model-based quantitative impact assessment of local, regional and nal policies up to Policy makers and other stakeholders will be strongly involved in the process, learn from experiences in other regions and gain a deeper understanding of the impact of policy instruments and their specific design. They are involved in the project through policy group meetings, workshops, interviews and webinars targeted to the fields of assistance in policy development, capacity building and dissemin. Acknowledgement This project has received funding from the European Union's Horizon 2020 research and innov programme under grant agreement No Funded by the Horizon 2020 Programme of the European Union Legal Notice The sole responsibility for the contents of this public lies with the authors. It does not necessarily reflect the opinion of the European Union. Neither the INEA nor the European Commission is responsible for any use that may be made of the inform contained therein. All rights reserved; no part of this public may be translated, reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the written permission of the publisher. Many of the designs used by manufacturers and sellers to distinguish their products are claimed as trademarks. The quot of those designs in whatever way does not imply the conclusion that the use of those designs is legal without the consent of the owner of the trademark. 2

3 Years of implement: March 2015 October 2017 Client: INEA eb: Project consortium: Energy Economics Group, Institute of Energy Systems and Electrical Drives, Technische Universität ien Fraunhofer Institute for the advancement of applied research Technical University Denmark Institute for Resource Efficiency and Energy Strategies Energy Cities OÖ Energiesparverband EE Energy Engineers GmbH Gate 21 City of Litomerice Instituto de Engenharua Mecanica e Gestao Industrial Agentia Pentru Management ul Energiei si Protectia Mediului Brasov 3

4 Contents 1. Introduction Assumptions and input data Modelled current system Model calibr/ Status quo of production Demand status-quo and projection Hourly demand profile of the district heating network Energy demand projection for Brasov Heat saving costs of the building stock in Brasov Individual supply technologies GIS based analysis of the Brasov DH system Scenario definition Scenario 1: Reference Scenario Parameters for simple socio economic calcul Parameters for private economic calcul Scenario 2: High share of gas fired DH Results Scenario 1: Reference Scenario Scenario 2: High share of gas fired DH Conclusions References

5 1. Introduction D2.2 - Assessment of local feasible RES-H/C utilis The heat supply in Brasov has gone through severe changes during the last decades. Its initial purpose and technical solution was, supplying the industry with steam and secondary hot water for the popul. In the 1990 s until the beginning of the 2000 s a big number of households where connected to the district heating system supplied by a coal fired cogener power plant. The industry to which the steam was supplied was completely shut down in 1990, thus the system became ineffective and has huge infrastructure problems (oversized diameters of transport pipelines, popul supply pipelines with unjustified long trails, big network losses). Due to this unsecure and interrupted supply many consumers disconnected from the system changing to individual natural gas boilers. During the years 2010 to 2012 the old coal fired plant was exchanged by modern CHP gas engines. Meanwhile more than one third of the transport and one fifth of the distribution network has been rehabilitated but the network remained over-dimensioned and big losses are a severe problem. Required high investments and the ever decreasing number of remaining costumers would lead to a high price for heat. Currently the district heating tariff for private households is subsidised by the municipality and it is tried to convince former costumers to reconnect to the district heating system. In the last 25 years, a lot of scenarios were tried in order to revitalise the DH system, but the lack of confidence in the possibility of building a new modern system resulted in loss of consumers. Another cause was the law that allowed installing heating units for buildings or apartments without restrictions. This process is relatively simple, as the popul in Brasov already has natural gas in the kitchen for cooking. There are no environment taxes for the individual heating in apartment buildings, although the chimneys are placed on the facade of each apartment. During the next period, starting with September 2016, the Local Counsel decided to reorganize the DH system in order to ensure a system more efficient for the popul. In this manner, the local authority can intervene with a larger financial contribution to the system`s support and revitaliz. There will be only one external heat producer, Bepco, which produces cogenerated heat with highefficient CHP gas engines at different sites: CHP Site Bepco Nord 1 CHP Site Bepco Nord 2 CHP Site Bepco Metrom and CHP Site Bepco Noua Transport, distribution and supply will be covered by a new structure that will be developed as a public service of Brasov Municipality and which also will produce heat for small local networks in 11 natural gas fired district thermal plants 5

6 2. Assumptions and input data D2.2 - Assessment of local feasible RES-H/C utilis The calculs performed for this report are examined by a combin of different tools and models and the consolid of the results in an Excel based spreadsheet tool called Least Cost Tool (LCT). For a detailed description of the LCT and the whole modelling framework see deliverable 2.4 of this project. The LCT compares costs of heat savings with the costs of supplying different building classes with district heat (DH) or with individual heat supply technologies. Main inputs into the LCT are: The price of District Heat and the price elasticity of the demand which is calculated in energypro model [1]. The assumptions and input data regarding this are shortly explained in Section 2.1. The heat demand calculs and heat saving costs per building class as well as the demand projections which are calculated with the Invert model [2]. This is explained in Section 2.2. Cost assumptions for individual supply technologies which are explained in 2.3 To allocate the buildings to different types of areas regarding availability or potential expansion of the current district heating system a GIS based analysis is performed which is explained in Section 2.4 Two different perspectives are considered for all calculs: Simple socio economic perspective: this perspective excludes energy taxes and VAT and assumes a low, socio-economic based interest rate. CO 2 costs are included as they are seen as an externality and not as an energy tax. Still this perspective does not represent a comprehensive socio economic view because real external costs are not considered and also other socio economic factors are not included. Private economic perspective: this perspective includes energy taxes and VAT and assumes a market based interest rate (private economic perspective). Subsidies for combined produced electricity are included. Also CO 2 costs are included as they are seen as an externality. The LCT performs iters to reflect changes in costs of the different supply technologies when heat-saving measures are implemented. In this report only the case study specific assumptions and input data will be explained. For further explan of the overall modelling framework see Deliverable Modelled current system To calculate a price for district heating the current DH system in Brasov is modelled in energypro and calibrated to current system data as far as possible. The system is modelled from a private economic perspective and therefore includes energy taxes and subsidies to represent the current situ. Figure 1 shows an older schematic map with the different parts of the DH system in Brasov. 6

7 Figure 1 District heating network in Brasov The four different sites are modelled in energypro to depict each of the DH-systems. Figure 2 shows the site overview of the different DH systems as they are modelled. Each site consists of different supply types like CHP gas engines and natural gas heat only boilers. Figure 2 Sites of the district heating network in Brasov 7

8 For each of the four sites the supply units have to cover the respective heat demand and heat losses. The electricity consumption of the plants and pumps in the different site has to be covered by own production or by purchasing the electricity on the Romanian ROPEX market. Although each network can provide heat at different costs the economic view depicts an overall view of the system. This means that one overall price for the supply of the heat to the costumers is calculated. Therefore the production costs of the supply units are calculated according to their marginal cost but including investments into the system undertaken from 2005 until now. Included operal costs are shown in Table 1: Table 1 Included operal costs for current system / model calibr Cost parameter Value Source Natural gas price for DH utility including energy tax 30,8 EUR/Mh Eurostat CO 2 emission costs for the DH utility 7,5 EUR/tCO 2 PRIMES Electricity price incl. tax for plants and pumps 80,7 EUR/Mh Eurostat Fixed oper costs (including oper, maintenance, administrative and personnel costs 12,5 EUR/Mh Own assumption Included revenues are shown in Table 2. The utility sells the produced electricity on the spot market and receives an additional bonus for combined produced electricity. Table 2 Included revenues for current system / model calibr Revenue parameter Value Source Electricity from the CHP units Spot market payment ROPEX CHP bonus 41 EUR/Mh ABMEE Included Investments are shown in Table 3. The private economic perspective includes a market based interest rate and shorter depreci times. Table 3 Investment Assumptions for current system / model calibr Investment assumptions Investments into CHP units completed from Investments into heat only units completed from Investments into transport network completed from (13 km out of 905 EUR/m) Investments into distribution network completed from (16 km out of EUR/m) Total investments into Substs from ( EUR each) Interest rate Lifetime [Years] Investment [EUR] Annuity [EUR] 7% % % % %

9 2.1.1 Model calibr/ Status quo of production Table 4 gives an overview on the status quo of produced, lost and delivered heat within the different networks. Table 4 Final energy demand district heating networks in Brasov (ref. to 2014) DH system Supply from plant [Mh] Transmission heat losses [Mh] Final energy demand provided to consumers [Mh] Heat losses % Nord ,6% Metrom ,1% Noua ,1% CT ,9% Total Table 10 gives an overview on the results of some technical parameters and data provided by the utilities. The results show some interesting details: The power to heat ratio of the installed gas engines does not reflect the provided data for the heat and power output. This may occur because the engines are working in an electricity led mode and the excess heat is cooled away. Or the engines do run in a way not reflecting the nominal oper point. A heat rejection unit was introduced into the model that allows cooling away excess heat when heat production costs are negative at high electricity prices. Using the ROPEX 2014 data there are not enough hours with high electricity prices and the electricity production does not reflect the provided data as can be seen in Table 10. Table 5 Technical results of the current status model. Parameter Model Results Provided data Introduced heat [Mh_th] Rejected heat (when allowed) [Mh] Produced electricity [Mh_el] (when no heat rejection is allowed) ( ) Introduced natural gas [Mh] (when no heat rejection is allowed) ( ) Emissions of the DH system [tco 2 ] (when no heat rejection is allowed) Emissions allocated to heat gener [tco 2 ] (IAE Method) (83 200) The outcomes of the economic analysis are given below. The given long run heat production cost refers to the marginal costs of heat production (no heat losses) including investments stated in Table 3. The given long run heat selling price gives the costs at which the heat has to be sold to the 9

10 costumer (including heat losses) to cover the DH-system costs including the investments stated in Table 3. It can be seen that the short run heat gener costs are relatively cheap. The long run costs are very high due to high completed investments. Additionally the high network loss results in a high required selling price compared to the gener costs. Table 6 Economic results of the current status model Economical Parametr Short run heat production costs Short run heat selling price Long run heat production costs (including completed investments) Long run heat selling price (including completed investments) Result 24,4 EUR/Mh 58,9 EUR/Mh 58,6 EUR/Mh 142 EUR/Mh 2.2 Demand status-quo and projection The status quo of the overall heat demand comes from the emission inventory performed by ABMEE. Also a detailed register of buildings and respective number and square meters for different building categories are available. This data is used to generate a building stock for the bottom up technoeconomic Invert-model. This model calculates the heat demand of building types according to specified geometry data and U-Values. The model is calibrated with the building stock data provided by ABMEE. The model is then used to project the heat demand under different scenario assumptions Hourly demand profile of the district heating network The hourly demand profile has been generated by fractioning the annual demand of the district heating network into hourly demand values. To do so 75% of the district heating demand has been modelled to be linear dependent on ambient temperatures accounting for space heating. A threshold value of 10 C ambient temperature is used. Above this threshold no space heat is demanded. The residual 15%-share of the district heating demand is modelled independent from ambient temperatures, assuming that it mainly is residential hot water demand. Region-specific hourly profiles for ambient temperature, wind and solar radi for the loc: 45.69N/ 25.57E are used. Figure 3 shows the so generated profile for the DH System Nord in Brasov. Network losses of the DH systems are assumed to be constant throughout the year. 10

11 Figure 3 Annual heat demand profile for the Brasov Nord DH system Energy demand projection for Brasov Based on the building stock two energy demand projections are calculated using the bottom-up model INVERT/EE-Lab. The projections are based on a current policy scenario for Romania. The first projection reflects the heat development only due to construction of new buildings and the demolition of old buildings but no of buildings. The resulting projection of the final energy demand for space heating and hot water per building type category is given in Figure 4. A decrease in heat demand from about Gh in 2014 to in 2030 (-6,4%) and to little less than Gh in 2050 (-18%) can be observed. This projection is used as input for the LCT. Heat savings will be calculated within the LCT according to their costs compared with DH and individual supply technologies. 11

12 Figure 4 Final energy demand projection for buildings in Brasov including only construction and demolition of buildings but no heat saving measures [Gh]. The second projection reflects the heat development including implemented heat savings. This projection includes investment decisions and viability of heat savings in the considered time period. Figure 5 Final energy demand projection for buildings in Brasov including heat saving measures [Gh]. 12

13 2.2.3 Heat saving costs of the building stock in Brasov D2.2 - Assessment of local feasible RES-H/C utilis For 10 different building categories and three different age classes (very old, old, normal) costs of 10 different depths are calculated. For all of these s a resulting heat demand is calculated. This makes it possible to calculate additional costs for and the respective heat savings per building to calculate heat saving costs per m² of living area for all building classes. Table 7 shows the costs of for the different options for very old buildings and Table 8 shows the respective heat demand after performing the. Table 7 Total cost of including taxes for very old buildings [EUR/m²] 1 Building category maint enanc e standa rd Single Family House 83,6 141,9 124,1 125,0 125,2 126,6 130,8 135,1 152,1 164,7 Single Family House 83,5 136,0 123,8 124,2 124,7 125,3 128,2 131,3 144,0 150,8 detached Multifamily House small 77,3 123,3 111,1 111,2 111,5 113,0 115,5 118,6 127,3 134,8 (around 400m²) Multifamily House large (around ,7 58,8 45,0 46,6 49,8 50,3 48,7 51,8 69,1 73,5 m²) Offices public 21,0 41,6 33,6 33,6 35,4 36,7 40,2 38,1 51,5 66,0 Offices private 51,3 98,1 79,7 83,8 86,8 94,1 87,8 91,4 114,0 150,4 holesaleretai 26,1 47,5 41,3 41,3 42,6 44,3 46,8 52,6 51,3 60,8 l Hotels / Restaurants 26,9 53,7 43,1 43,1 45,6 47,7 52,7 49,3 66,5 85,2 Health 25,8 53,5 42,8 42,8 44,3 46,4 49,8 48,4 69,0 85,9 Educ 39,9 67,2 60,2 64,8 80,7 61,5 62,3 64,1 73,1 92,7 Other 39,9 67,2 60,2 64,8 80,7 61,5 62,3 64,1 73,1 92,7 Table 8 Specific heat demand in very old buildings after performing the respective [kh/m²] 2 Building category Single Family House Single Family House detached Multifamily House small (around 400m²) maint enanc e standa rd ,2 71,9 106,0 104,9 103,5 97,3 88,3 79,2 61,0 48,7 277,3 77,1 106,3 105,8 105,2 102,4 95,2 85,8 65,3 53,5 228,7 62,5 91,1 90,7 89,2 83,3 76,5 69,2 53,0 43,9 1 Calculs performed with Invert-model[2] 2 Calculs performed with Invert-model[2] 13

14 Multifamily House large (around ,1 46,9 77,1 73,0 68,4 61,7 54,9 49,7 35,8 28,2 m²) Offices public 90,6 35,9 61,7 61,7 54,7 50,8 45,7 37,6 30,8 21,4 Offices private 212,9 72,5 150,4 131,4 121,5 109,3 89,2 76,8 59,9 40,3 holesaleretai l 143,2 71,8 102,9 102,9 99,2 90,4 84,1 77,5 64,0 56,4 Hotels / Restaurants 113,6 44,2 78,1 78,1 68,7 62,7 56,7 46,2 37,6 25,4 Health 191,3 115,7 149,6 149,6 145,7 137,0 129,7 118,2 108,1 94,5 Educ 143,4 42,9 87,8 80,5 74,0 60,9 53,2 45,2 36,3 27,1 Other 143,4 42,9 87,8 80,5 74,0 60,9 53,2 45,2 36,3 27,1 2.3 Individual supply technologies Table 9 Investment costs for different sizes of individual supply technologies including taxes [EUR/k] shows the investment costs for individual supply technologies used for the calcul of costs for heat within the LCT. Table 9 Investment costs for different sizes of individual supply technologies including taxes [EUR/k] 3 Individual supply technology Oil central Gas central ood pellets central Heat pump air/water Heat pump brine/water (Size [k]) cost [EUR/k] (6k) 11EUR/k (10k) 214.6EUR/k (10k) 135.3EUR/k (10k) 660.8EUR/k (10k) 471.3EUR/k (Size [k]) cost [EUR/k] (7k) 12EUR/k (20k) 191.1EUR/k (20k) 120.5EUR/k (20k) 561.4EUR/k (20k) 438.7EUR/k (Size [k]) cost [EUR/k] (8k) 13EUR/k (35k) 156EUR/k (35k) 98.4EUR/k (35k) 412.2EUR/k (35k) 389.8EUR/k (Size [k]) cost [EUR/k] (9k) 14EUR/k (100k) 128.3EUR/k (100k) 80.9EUR/k (100k) 265.2EUR/k (100k) 324.5EUR/k (Size [k]) cost [EUR/k] (10k) 15EUR/k (200k) 105.6EUR/k (200k) 66.6EUR/k (200k) 179.1EUR/k (200k) 248.1EUR/k 2.4 GIS based analysis of the Brasov DH system The LCT calculates the optimal mix of the different supply options for four different types of areas which are defined with GIS based analysis. The results are shown in Figure 6 to Figure 8 District heating areas Next-to-DH areas Individual areas Scattered Buildings/ Individual buildings 3 Data from Invert-model database[2] 14

15 District heating areas are defined as the area 50 m around existing (operating and non-operating) distribution network. For the buildings not supplied by district heating but located in district heating areas it is necessary to invest only in connecting pipes and heat exchangers to be able to connect to district heating. Next-to-district heating areas are sharing a border with existing district heating areas and are defined as the area 1km around existing transport network excluding the district heating area. For the buildings located in Next-to-DH areas, it is necessary to invest in distribution pipes, connecting pipes and heat exchangers to be able to connect to district heating. Buildings within this area whose 10 nearest neighbours are altogether farer away than 1 km (mean distance of more than 100 m between the 10 nearest neighbours) will not be connected in case of an expansion. They are classified into the group of individual buildings. The individual area is defined as the area outside the next-to-dh areas. The individual area is not supplied by district heating and is not sharing a border with existing district heating area. For the buildings located in Individual areas, it is necessary to invest in transmission pipes, distribution pipes, connecting pipes and heat exchangers to be able to connect to district heating. Scattered buildings area represents buildings across the municipality which are not close enough to other buildings. All buildings in the next-to-dh area and in the individual area which have less than 10 buildings within a range of 1 km are classified as individual buildings. The expansion of district heating to these buildings is not considered to be an alternative. Figure 6 shows the areas defined as district heating areas and the buildings that are located within each area. Yellow dots represent buildings already connected to the respective DH-System. As the DH-Systems Metrom and Nord are touching each other they are seen as one DH-area in a future system. The Noua DH-System in the south of Brasov is considered as another DH area. All areas supplied by the CT thermal units are also seen as one DH area. 15

16 Figure 6 Defined District heating-areas, buildings and connected buildings in Brasov The next-to-district heating areas and the buildings related to these areas are shown in Figure 6. As the CT thermal units only connect buildings through a distribution network they are not surrounded by a next-to-dh area. 16

17 Figure 7 Areas defined as next-to-district heating-area. Figure 7 shows the buildings assigned to the individual area and the ones classified as scattered/ individual buildings. 17

18 Figure 8 Buildings defined as individual areas and individual users. 18

19 3. Scenario definition D2.2 - Assessment of local feasible RES-H/C utilis The scenario assumptions in this section describe the different system configurs that could be achieved until For each scenario two perspectives are analysed as stated in Section Scenario 1: Reference Scenario The reference scenario aims to reflect a development when no certain additional action will be undertaken. For the individual heating systems no restriction is foreseen in the Reference scenario. For the calcul of the DH-price following system assumptions are taken into account: Overall heat demand development due to demolition and construction of new buildings according to the Invert projection for 2030 (-6,4%) and 2050 (-18%) The total distribution and transport network not ated in the last 10 years will be renewed until 2030 Since 2005 completed and additional investments into network until 2030 are included Due to this the network losses in 2030 will decrease to 10% of the produced heat. The heat saved through reduction of network losses can be delivered to reconnected costumers This assumptions result in the heat demand for the district heating system as stated in Table 10. Table 10 Energy demand 2030 in Brasov district heating networks according to reference Scenario DH system Supply from plant [Mh] Heat losses [Mh] Energy demand provided to consumers [Mh] Heat losses [%] Nord % Metrom % Noua % CT % Total % Parameters for simple socio economic calcul Table 11 shows the economic parameters and Table 12 the total (completed and additional) investments into the district heating systems until 2030 used for the simple socio economic calcul. Table 11 Parameters for the reference scenario 2030 for simple socio economic calcul Parameter for Simple socio economic calcul Value Source Natural gas price for District Heating utility excluding taxes 31,1 EUR/Mh Eurostat CO 2 emission costs for the District Heating utility 31,5 EUR/tCO 2 PRIMES Electricity price excl. tax for plants and pumps 71,7 EUR/Mh Eurostat Annual average electricity spot market price 32 EUR/Mh CHP Bonus for produced electricity 0 EUR/Mh Fixed oper costs for District Heating (including 12,5 EUR/Mh Own 19

20 oper, maintenance, administrative and personnel costs assumption Biomass (wood pellets) price for individual supply excl. taxes 26,8 EUR/Mh Eurostat Natural gas price individual supply excluding taxes 31,1 EUR/Mh Eurostat Oil price for individual supply excluding taxes 118,7 EUR/Mh Eurostat Electricity price for households excluding taxes 90,6 EUR/Mh Eurostat Overall interest rate 4% Depreci time for individual supply technologies 22 years Depreci time for heat savings 40 years Depreci time for District Heating supply units 20 years Depreci time for District Heating network 40 years Table 12 Investment Assumptions for simple socio economic calcul Investment assumptions Total investments into CHP units from Total investments into heat only units from Total investments into transport net from Total investments into distribution net from Total investments into Substs from Interest rate Lifetime [Years] Investment [EUR] Annuity [EUR] 4% % % % % Parameters for private economic calcul Table 13 shows the economic parameters used for the private economic calcul and Table 14 the total (completed and additional) investments into the district heating systems until Table 13 Private economic calcul parameters for the reference scenario 2030 Parameter for Simple socio economic calcul Value Source Natural gas price for District Heating utility including taxes 45,3 EUR/Mh Eurostat CO 2 emission costs for the District Heating utility 31,5 EUR/tCO 2 PRIMES Electricity price incl. taxes for plants and pumps 81,5 EUR/Mh Eurostat Annual average electricity spot market price 32 EUR/Mh CHP Bonus for produced electricity 41 EUR/Mh ABMEE Fixed oper costs for District Heating (including Own 12,5 EUR/Mh oper, maintenance, administrative and personnel costs assumption Biomass (pellets) price for individual supply incl. taxes 32,2 EUR/Mh Eurostat Natural gas price individual supply including taxes 77,7 EUR/Mh Eurostat Oil price for individual supply including taxes 256,1 EUR/Mh Eurostat Electricity price for households including taxes 149,8 EUR/Mh Eurostat Overall interest rate 7% Depreci time for individual supply technologies 15 years Depreci time for heat savings 20 years Depreci time for District Heating supply units 15 years Depreci time for District Heating network 20 years 20

21 Table 14 Investment assumptions district heating system for private economic calcul Investment assumptions Total investments into CHP units from Total investments into heat only units from Total investments into transport net from Total investments into distribution net from Total investments into Substs from Interest rate Lifetime [Years] Investment [EUR] Annuity [EUR] 7% % % % % Scenario 2: High share of gas fired DH The high share of DH scenario reflects the situ when a high share of buildings can be connected within the defined DH areas. For the individual heating systems no restriction is foreseen in this scenario. For the calcul of the DH-system following assumptions are taken into account in the model: The total distribution and transport network not rehabilitated in the last 10 years will be renewed until 2030 Since 2005 completed and additional investments into network until 2030 are included Due to this the network losses in 2030 will decrease to 10% of the produced heat. This scenario assumes that in the district heating areas as much costumers can be additionally connected that the total capacity of the current supply units is utilised This assumptions result in the heat demand for the district heating system as stated in Table 15. Table 15 Energy demand 2030 in Brasov district heating networks according to scenario with high share of gas fired DH DH system Supply from plant [Mh] Heat losses [Mh] Energy demand provided to consumers [Mh] Heat losses [%] Nord % Metrom % Noua % CT % Total % Investment assumptions and economic parameters for simple socio economic calcul and private economic calcul for scenario 2 are equivalent to scenario 1. 21

22 4. Results D2.2 - Assessment of local feasible RES-H/C utilis 4.1 Scenario 1: Reference Scenario This scenario applies the least cost combin of heat savings, district heat and individual supply. No limits in the implement are assumed and no further restrictions for the supply technologies are given. Two different perspectives as stated in Section 2 are calculated. Table 16 compares the outcomes of the two different perspectives whereas in the following subsections the specific results of the two perspectives are given. Table 16 Comparison of parameters for Scenario 1 form simple socio economic calcul and private economic calcul System Parameter Current State Least cost Combin simple socio economic calcul Least cost Combin private economic calcul Total system costs reduction for space heating and domestic hot water 100% -38% -41% Demand reduction due to heat savings 100% -57% -61% Overall CO 2 emissions for space heating and domestic hot water tco tco tco 2 Share of RES in demand for space heating and domestic hot water 0,2% 2,2% 31,7% Share of demand for space heating and domestic hot water supplied by DH 2,8% 0% 0% Figure 9 compares the result of the Least Cost Tool for status quo with the outcomes of scenario 1. It can be seen that heat savings are the cheapest option in all building classes. Due to no limit of heat savings all possible savings are implemented leading to an optimal overall heat demand reduction of 57% in simple socio economic calcul and an optimal overall heat demand reduction of 61% in private economic calcul. 22

23 Figure 9 Comparison of least cost combin for total building stock in 2030 under simple socio economic calcul and private economic calcul Results from simple socio economic calcul: Table 16 and Table 17 give the technical and the economical results for the calculs for the DH system. In this scenario the heat for the DH is mainly produced by natural gas boilers because running the CHP units without the CHP bonus is not economical feasible. Therefore the costs for district heat are very high. Table 17 Technical results of 2030 reference scenario from simple socio economic perspective Parameter Results 2030 Scenario 1, Simple socio economic calcul Introduced heat [Mh_th] Rejected heat [Mh] - Produced electricity [Mh_el] Introduced fuel [Mh] Emissions of the DH system [tco 2 ] Emissions allocated to Heat gener [tco 2 ] (IEA Method) Table 18 Economic results of 2030 reference scenario from simple socio economic perspective Economical Parametr Included investments Result Long run heat production cost Investments into supply and network from 95,5 EUR/Mh 2005 to 2030 Long run heat selling price Investments into supply and network from 106 EUR/Mh 23

24 Capital cost share Specific CO 2 emissions heat D2.2 - Assessment of local feasible RES-H/C utilis 2005 to ,9 EUR/Mh 0,2 t/mh Figure 10 shows the Least cost combin of heat saving and heating system exemplary for old single and very old multifamily houses. Figure 10 Least cost combin exemplary for old SFH and very old MFH in 2030 from simple socio economic perspective Figure 11 shows the outcomes for the different areas. It can be seen that in all areas the combin of heat savings with natural gas boiler is the cheapest option except for the individual users which have no natural gas network available. In this case heat savings in combin with a biomass boiler is the cheapest combin. 24

25 Figure 11 Least cost combin for the different Areas in 2030 from simple socio economic perspective Results of private economic calcul Table 19 and Table 20 give the results of the Private economic calcul. The included CHP bonus of 41EUR is not enough to run the CHP plants economically. Therefore the CHP plants only run when necessary and almost the whole share is produced by the gas boilers. This together with the higher interest rates and the shorter depreci time makes district heat very expensive under these conditions. Table 19 Technical results of 2030 Scenario 1 from private economic perspective Parameter Results 2030 Scenario 1, Private economic calcul Introduced heat [Mh_th] Rejected heat [Mh] - Produced electricity [Mh_el] Introduced fuel [Mh] Emissions of the DH system [ tco2 ] Emissions allocated to Heat gener [tco 2 ] (IEA Method)

26 Table 20 Economic results of 2030 Scenario 1 from private economic perspective Economical Parametr Included investments Result Long run heat production cost Investments into supply and network from 2005 to EUR/Mh Long run heat selling price Investments into supply and network from 2005 to EUR/Mh Capital cost share 85,3 EUR/Mh Specific CO 2 emissions heat 0,2 t/mh Figure 12 shows the Least cost combin of heat saving and heating system exemplary for old single and very old multifamily houses. Compared to simple socio economic calcul in this case biomass boilers are the cheapest combin for buildings where they are applicable. For bigger buildings where biomass boilers are not possible natural gas is the cheapest combin. Figure 12 Least cost combin for old SFH and very old MFH in 2030 from private economic perspective. Figure 13 shows the outcomes of the Least Cost Tool for the different areas. In all areas biomass boilers are the cheapest combin with heat savings for smaller residential buildings and natural gas boiler in combin with heat savings in bigger buildings. 26

27 Figure 13 Least cost combin for total building stock in 2030 from private economic perspective 4.2 Scenario 2: High share of gas fired DH Results from simple socio economic perspective: Table 21 Technical results of 2030 Scenario 2 from simple socio economic perspectiveand Table 22 Economic results of 2030 Scenario 2 from simple socio economic perspectivegive the technical and the economical results for the calculs for the DH system from simple socio economic perpsective. Due to the higher number of costumers and the economic conditions in simple socio economic calcul the heat selling price drops significantly compared to Scenario 1. Still individual technologies are cheaper because of the high investments that have to be done into the DH system. Still gas fired CHP plants cannot work economic without subsidies. Table 21 Technical results of 2030 Scenario 2 from simple socio economic perspective Parameter Results 2030 Scenario 2, Simple socio economic calcul Introduced heat [Mh_th] Rejected heat [Mh] - Produced electricity [Mh_el] Introduced fuel [Mh] Emissions of the DH system [tco 2 ] Emissions allocated to Heat gener [tco 2 ] (IEA Method)

28 Table 22 Economic results of 2030 Scenario 2 from simple socio economic perspective Economical Parametr Included investments Result Long run heat production cost Investments into supply and network from 2005 to ,6 EUR/Mh Long run heat selling price Investments into supply and network from 2005 to ,6 EUR/Mh Capital cost share 21,2 EUR/Mh Specific CO 2 emissions for Heat 0,2 t/mh As district heating is not competitive from this perspective in this Scenario the results for the cheapest combin of savings and supply for the buildings are the same as in Scenario 1. Results from private economic perspective: Table 23 and Table 24 give the technical and the economical results for the calculs for the DH system from private economic calcul. This perspective leads to an even higher price for DH why DH is not competitive with combins of heat savings with individual supply options. Table 23 Technical results of 2030 Scenario 2 from private economic perspective Parameter Results 2030 Scenario 2, Private economic calcul Introduced heat [Mh_th] Rejected heat [Mh] - Produced electricity [Mh_el] Introduced fuel [Mh] Emissions of the DH system [tco 2 ] Emissions allocated to Heat gener [tco 2 ] (IEA Method) Table 24 Economic results of 2030 Scenario 2 from private economic perspective Economical Parametr Included investments Result Long run heat production cost Investments into supply and network from 2005 to EUR/Mh Long run heat selling price Investments into supply and network from 2005 to EUR/Mh Capital cost share 36,9 EUR/Mh Specific CO 2 emissions for Heat 0,2 t/mh As district heating is not competitive from this perspective in this Scenario the results for the cheapest combin of savings and supply for the buildings are the same as in Scenario 1. 28

29 5. Conclusions D2.2 - Assessment of local feasible RES-H/C utilis In course of modelling the heating system of the municipality of Brasov we analysed the economic efficiency as well as the CO 2 reduction potentials of various options to save heat and supply heat in the buildings. In the current analysis we focus on two scenarios: a reference scenario, where we assume that until 2030 the not yet renewed part of the network gets renewed, which reduces network losses from currently around 50% to 10%. This rehabilitated heat can be delivered to reconnected costumers. For this situ we analyse least cost combins of heat saving and heat supply for different types and ages of buildings in different locs in the municipality. In a second scenario we assume that in the district heating areas as much costumers can be additionally connected to the district heating network that the total capacity of the current supply units is utilised and again we analyse the least cost combins of heat saving and heat supply for different types and ages of buildings in different locs. The analysis shows that at least a certain amount of heat savings are the cheapest option for all buildings both in simple socio economic calcul (socio-economic conditions, however not taking into account external costs) and private economic calcul (private-economic conditions). The level of ambition of the savings hereby varies between building categories and age of the buildings. hen not taking into account energy taxes and assuming depreci times in the range of the lifetime of supply systems or measures, as is the case under simple socio economic calcul, the cheapest option for all buildings is heat saving in combin with a natural gas boiler followed saving in combin with an air source heat pump when assuming a high COP of 3.3. Assuming a low COP of 2.3 for air source heat pumps makes savings in combin with biomass boilers the second least cost combin. hen taking into account energy taxes and shorter depreci times, as is the case for private economic calcul (private economic perspective), biomass boilers are the cheapest supply option in combin with heat savings followed by air-source heat pumps when assuming a low COP of 2.3. In that case heat pumps and biomass boilers have heat gener costs close to each other and their economic feasibility depends on assumed taxes on energy carriers. If no restrictions on the use of certain supply technologies in certain parts of the municipality as well as in certain types of buildings are assumed, these results apply for the whole building stock. In the current scenarios district heating is not feasible from none of the two perspectives. But so far no calculs have been performed that underlie a certain minimal share of renewable energy in the heating system. Additionally, the usability of heat pumps and biomass systems in different types of buildings and different areas in the municipality has to be discussed and taken into account in the calculs. If biomass and decentral heat pumps are no solution for the densely populated part of the city, district heating may be the only option to decarbonise substantially. If this is desired, viability can only be reached when grid losses can be reduced and high connection rates will be achieved. Additionally grid investments have to be subsidised due to their long run investment horizon. 29

30 6. References D2.2 - Assessment of local feasible RES-H/C utilis [1] Homepage of energypro model. Available at: (accessed on [2] Homepage of Invert/EE-Lab model. Available at: (accessed on ) 30